Network pharmacology goes beyond the traditional single-target approach by adopting a comprehensive systems biology perspective. This field studies the complex interactions within biomolecular networks, fundamentally changing our understanding of how drugs interact with the body. This chapter explores the fundamental concepts and applications of network pharmacology in drug target discovery and drug repurposing. We discuss how network pharmacology models the complex interrelationships between diseases, targets, and drugs through various biomolecular networks, including metabolic pathways, gene regulatory networks, protein interaction networks, and drug-target interaction networks. The review examines multiple analytical approaches, from traditional network analysis methods to advanced computational techniques such as similarity-based recommendation systems, network propagation algorithms, matrix decomposition, and graph neural networks. These methods enable the identification of new drug targets and the prediction of novel drug indications, particularly valuable in drug repurposing efforts. We highlight how network pharmacology leverages existing biological and chemical data to construct comprehensive biomolecular networks, offering insights into disease mechanisms and drug actions at a systems level. This approach not only enhances our understanding of complex diseases but also provides efficient strategies for drug development by identifying new applications for existing drugs, potentially reducing the time and cost of traditional drug discovery processes.